The dynamics of stochastic reaction networks within cells are inevitably modulated by factors
considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy …

Stochastic simulations of biochemical networks are of vital importance for understanding
complex dynamics in cells and tissues. However, existing methods to perform such …

Cellular processes are open systems, situated in a heterogeneous context, rather than
operating in isolation. Chemical reaction networks (CRNs) whose reaction rates are …

Abstract Continuous Time Bayesian Networks (CTBNs) provide a powerful means to model
complex network dynamics. How-ever, their inference is computationally demanding …

Biochemical processes within clonal cell populations exhibit a substantial degree of cell-to-
cell variability. While a fraction of the overall variability is due to the intrinsic stochasticity of …

Markovian population models are suitable abstractions to describe well-mixed interacting
particle systems in situation where stochastic fluctuations are significant due to the …

This thesis explores aspects of model specification and analysis for population dynamics
which arise when modelling complex interactions and communication structures in agent or …